We’ve just begun to scratch the surface of the impact of machine learning on the enterprise. Organizations are applying machine learning algorithms to business processes to automate manual tasks and identify patterns in transactional data to drive strategic decisions. Many applications are focused on efficiency and automation, but that trend is shifting. More and more businesses are using machine learning to develop disruptive new business models.

What does this mean for your organization? Plenty, according to two experts during a recent Deloitte and ASUG Webinar, Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes. Leading the Webinar from Deloitte Consulting LLP were Darwin Deano, principal and chief officer for SAP Leonardo and Denise McGuigan, senior manager and Deloitte reimagine platform leader for Lights Out Finance. Darwin and Denise explained emerging trends, why enterprise resource planning (ERP) software is a hotbed for machine learning, and the potential impact on the workforce.

Making room for your digital twin

Machine learning unleashes the greatest possibilities for the enterprise by amplifying the best of human capabilities. It’s not about replacing humans; it’s about coexistence. In the future, there will be greater opportunities for people who can work with machines, take the information that’s produced, and do something meaningful with it.

Consider the concept of a digital twin. The digital twin is essentially the replication of a process system. In finance, payables transactions and record-to-report tasks require a copious number of journal entries that take a lot of time to input. Those tasks could all be reduced or even eliminated by a machine learning bot.

As a digital twin takes on transactional processes, individuals who performed those tasks are then able to focus their efforts on activities that make better use of their human skills by driving actionable insights. They would need to work alongside the digital twin and activate the resulting insight and analytics.

Unleashing data-driven ERP power

Before we give too much credit to the enabling power of machine learning, keep in mind that it all starts and ends with data. Machine learning is only as good as the algorithm, the algorithm is only as good as the data, and nobody knows the data about your core business better than the people who understand your ERP. Therefore, your people play key roles in identifying opportunities and driving the value of machine learning in your enterprise.

There are emerging roles across business and IT that will be critical to the success of not only designing and implementing, but operating, sustaining, and continuously improving investments in machine learning. Two of these roles are orchestrators and guardians.

Identifying orchestrators and guardians – the new stars

Before the advent of machine learning, organizations valued individual skills with a lot of emphasis on specialization. With machine learning, that emphasis shifts to the people who can put it all together – the orchestrators. Orchestrators help realize the value of machine learning. For example, a finance manager is a classic orchestrator. Finance managers know how order-to-cash flows into the central finance operation and how each individual department interacts with finance. For any machine learning scenario in finance, this manager would help put it all together.

The guardians monitor the effectiveness of machine learning to validate that your model works and to address any uncertainty about machine-driven actions. They’ll safeguard the audit trail, assess the evolution of data, and determine what adjustments need to be made. A supply chain director is a very good guardian who can filter out extraneous noise and verify the merits of machine learning scenarios. These roles and constructs will be increasingly important going forward.